Harvey Cutler

Building Small City and Town Sams and CGE Models

In this paper we attempt to describe both the data sources and organizational methods that allow for effective and easily created SAMs and regional computable general equilibrium (CGE) models. Small cities of around 100,000 people will face very different constraints than a town of 2000 people. Unfortunately, most CGE models typically describe relatively large geographical areas and are therefore not able to capture the uniqueness of individual cities within the region. An illustrative example using these methods demonstrates that the economic impacts vary substantially over different municipalities to the same economic shock.

Market recycling in labor-intensive goods, flying-geese style: an empirical analysis of East Asian exports to the U.S.

Abstract The United States plays the key role of market provider for less developed nations. Specifically, the U.S. allows developing nations to export manufactures, notably labor-intensive goods, into its market. Such a policy allows these nations to pursue export-led growth. East Asian prosperity has been built upon the U.S. trade stance, beginning with Japan in the early postwar era. Both the NIEs and the ASEAN-4, and most recently China, followed Japan on this development path. As a result, a sequential pattern of “market recycling” has occurred in the tradition of the “flying geese” model of catch-up development. This paper offers an empirical examination of the time-series nature of the recycling phenomenon. Utilizing cointegration analysis, we analyze the timing of market recycling.

The Impact of Specific-Sector Changes in Employment on Economic Growth, Labor Market Performance and Migration

It is common in empirical regional economics to use total employment as an explanatory variable while investigating issues such as the level and distribution of income and migration. This paper argues that sector-specific changes in employment and labor market performance can have different effects on economic growth, the collection of tax revenue, migration, and the level and distribution of household income. As such, it is important to model sectors separately. We find that expansions in employment opportunities for a high-wage sector such as computer manufacturing or bioengineering, a medium-wage sector manufacturing, and the lower-wage sector of retailing have differing economic consequences for a small city. We use a data intensive computable general equilibrium model to obtain these results.

The Centerville Virtual Community: a fully integrated decision model of interacting physical and social infrastructure systems

Abstract Enhancing community resilience in the future will require new interdisciplinary systems-based approaches that depend on many disciplines, including engineering, social and economic, and information sciences. The National Institute of Standards and Technology awarded the Center for Risk-Based Community Resilience Planning to Colorado State University and nine other universities in 2015, with the overarching goal of establishing the measurement science for community resilience assessment. The Centerville Virtual Community Testbed is aimed at enabling fundamental resilience assessment algorithms to be initiated, developed, and coded in a preliminary form, and tested before the refined measurement methods and supporting data classifications and databases necessary for a more complete assessment have fully matured. This paper introduces the Centerville Testbed, defining the physical infrastructure within the community, natural hazards to which it is exposed, and the population demographics necessary to assess potential post-disaster impacts on the population, local economy, and public services that are described in detail in the companion papers of this Special Issue.

The Demand for Nominal and Real Money Balances in a Large Macroeconomic System

Cointegration has become a popular empirical technique used to estimate the existence and stability of money demand relationships. A common approach has been to estimate a single equation system with real money balances (Ml), real income and an interest rate, although Hafer and Jansen [13], Friedman and Kuttner [10] and Stock and Watson [29] find only minimal support for this specification. Baba, Hendry and Starr [6] estimate a more complicated Ml relation by including specific opportunity cost variables and find stronger support for the Ml relation using post WWII data. There have been four reasons put forth to explain the lack of a cointegrating relation between Ml, real income and the interest rate. Stock and Watson [29] conclude that a stable money demand relation exists in data from 1900-89 but not for the post-war period alone. Their explanation is that sufficient variation exists in the longer sample to identify money demand, but excessive multicollinearity among variables during the post-war period prevents unique identification. Baba, Hendry and Starr [6] (BHS) maintain that misspecification of the Ml relation is the reason for poor results. They augment the money demand function with inflation, a measure of long term bond yield and risk, and learning curve weighted yields on newly introduced Ml and M2 assets. BHS claim their specification is able to account for the missing money period of 1975-76, the velocity decline of 1982-83 and the Ml explosion of 1985-86 while standard Ml models cannot. Friedman and Kuttner [10] offer a third reason why the simple money demand equation fails. They estimate a single equation model for several periods and conclude that a money demand vector exists over the 1960.2-79.4 period for Ml. However, when data is included

The Demand for M1 in a Large Macroeconomic System: Evidence from Cointegration Analysis

Abstract Most cointegration analyses in the literature fail to find support for a simple money demand (M1) relationship. The typical reasons for this lack of support are excessive multicollinearity, misspecification and a general breakdown of the money market. We imbed the money market in a system containing markets for consumption, investment and imports. The gains in efficiency and reduced bias from this full system approach results in a substantial improvement in the performance of the money market. We also find that Federal ReserveAEs targeting of aggregate reserves can lead to disequilibrium in the money market.

Forecasting in a large macroeconomic system

This paper examines the efficiency gains yielded from estimating multiple equation cointegrated systems as compared to their single equation counterparts. In particular, this paper is concerned with the ability of utilizing the cointegrating information to improve forecasting performance. Recently an inability to improve forecasts of real income once money demand error correction terms were introduced has been used to argue that the M2 relationship had broken down during the early 1990s. However, the results suggest that once the underlying responses of variables are more closely investigated, the behaviour of M2 has remained stable.

Integrating engineering outputs from natural disaster models into a dynamic spatial computable general equilibrium model of Centerville

Abstract A dynamic spatial computable general equilibrium (DSCGE) model is constructed that describes how engineering and economic models can be integrated to assess the economic, demographic, and fiscal impacts of disasters. This paper has two objectives. First, we introduce the DSCGE model and describe how it is calibrated specifically for Centerville. Second, to demonstrate the analytic flexibility of the DSCGE platform, we present economy-wide prompt effects from simulations involving spatially circumscribed shocks to Centerville’s building portfolio and transportation infrastructure, and then detail dynamic economy-wide effects from simulations involving combinations of infrastructure damage and adjustments to the economic behavior of agents. We conclude with a discussion of the technical challenges ahead.

Understanding the Unique Impacts of Economic Growth Variables

The paper uses a computable general equilibrium (CGE) model for a small city to examine how expansions in export and local sectors, changes in total factor productivity (TFP), and growth in population impact an economy. We examine the effects of each source of growth and find that the level and distribution of economic activity vary considerably. We also evaluate each source of growth in the context of a variety of policy metrics, which provide guidelines to policy makers, including the types of firms to be recruited in specific regions.

State of the research in community resilience: progress and challenges

Abstract Community resilience has been addressed across multiple disciplines including environmental sciences, engineering, sociology, psychology, and economics. Interest in community resilience gained momentum following several key natural and human-caused hazards in the United States and worldwide. To date, a comprehensive community resilience model that encompasses the performance of all the physical and socio-economic components from immediate impact through the recovery phase of a natural disaster has not been available. This paper summarizes a literature review of previous community resilience studies with a focus on natural hazards, which includes primarily models of individual infrastructure systems, their interdependencies, and community economic and social systems. A series of national and international initiatives aimed at community resilience are also summarized in this study. This paper suggests extensions of existing modeling methodologies aimed at developing an improved, integrated understanding of resilience that can be used by policy-makers in preparation for future events.